Stats chap 5

12. The weight of an object is an example of a. a continuous random variable. b. a discrete random variable. c. either a continuous or a discrete random variable, depending on the nature of the object. d. either a continuous or a discrete random variable, depending on the unit of measurement.

a. a continuous random variable.

4. A continuous random variable may assume a. any numerical value in an interval or collection of intervals. b. finite number of values in a collection of intervals. c. an infinite sequence of values. d. only the positive integer values in an interval.

a. any numerical value in an interval or collection of intervals.

5. A description of the distribution of the values of a random variable and their associated probabilities is called a a. probability distribution. b. empirical discrete distribution. c. bivariate distribution. d. table of binomial probability.

a. probability distribution.

26. A production process produces 2% defective parts. A sample of five parts from the production process is selected. What is the probability that the sample contains exactly two defective parts? a. 0.0004 b. 0.0038 c. 0.10 d. 0.02

b. 0.0038

13. Four percent of the customers of a mortgage company default on their payments. A sample of five customers is selected. What is the probability that exactly two customers in the sample will default on their payments? a. 0.2592 b. 0.0142 c. 0.9588 d. 0.7408

b. 0.0142

1. Which of the following is a characteristic of an experiment where the binomial probability distribution is applicable? a. The experiment has at least two possible outcomes b. Exactly two outcomes are possible on each trial c. The trials are dependent on each other d. The probabilities of the outcomes changes from one trial

b. Exactly two outcomes are possible on each trial

27. When dealing with the number of occurrences of an event over a specified interval of time or space, the appropriate probability distribution is a a. Binomial distribution. b. Poisson distribution. c. Normal distribution. d. Hypergeometric probability distribution.

b. Poisson distribution.

14. Twenty percent of the students in a class of 100 are planning to go to graduate school. The standard deviation of this binomial distribution is a. 20. b. 16. c. 4. d. 2.

c. 4.

15. In the textile industry, a manufacturer is interested in the number of blemishes or flaws occurring in each 100 feet of material. The probability distribution that has the greatest chance of applying to this situation is the a. Normal distribution. b. Binomial distribution. c. Poisson distribution. d. Uniform distribution.

c. Poisson distribution.

21. Which of the following is not a property of a binomial experiment? a. The experiment consists of a sequence of n identical trials b. Each outcome can be referred to as a success or a failure c. The probabilities of the two outcomes can change from one trial to the next d. The trials are independent

c. The probabilities of the two outcomes can change from one trial to the next

19. Which of the following is not a characteristic of an experiment where the binomial probability distribution is applicable? a. The experiment has a sequence of n identical trials b. Exactly two outcomes are possible on each trial c. The trials are dependent d. The probabilities of the outcomes do not change from one trial to another

c. The trials are dependent

7. A measure of the average value of a random variable is called a(n) a. variance. b. standard deviation. c. expected value. d. coefficient of variation.

c. expected value.

18. The expected value of a discrete random variable a. is the most likely or highest probability value for the random variable. b. will always be one of the values x can take on, although it may not be the highest probability value for the random variable. c. is the average value for the random variable over many repeats of the experiment. d. is the value it is expected to assume in the next trial.

c. is the average value for the random variable over many repeats of the experiment.

25. The expected value for a binomial distribution is given by equation a. (n - 1)(1 - p). b. n(1 - p). c. np. d. (n - 1)p.

c. np.

9. A weighted average of the values of a random variable, where the probability function provides weights, is known as a. the probable value. b. the median value. c. the expected value. d. the variance.

c. the expected value.

22. In a binomial experiment a. the probability does not change from trial to trial. b. the probability changes from trial to trial. c. the probability could change from trial to trial, depending on the situation under consideration. d. the probability could change depending on the number of outcomes.

c. the probability could change from trial to trial, depending on the situation under consideration.

20. The expected value of a random variable is a. the value of the random variable that should be observed on the next repeat of the experiment b. the value of the random variable that occurs most frequently c. the square root of the variance d. None of these alternatives is correct.

d. None of these alternatives is correct.

24. The variance Var(x) for the binomial distribution is given by equation a. np(n - 1). b. np(1 - np). c. n(1 - p). d. np(1 - p).

d. np(1 - p).

2. A numerical description of the outcome of an experiment is called a a. descriptive statistic. b. probability function. c. variance. d. random variable.

d. random variable.

6. Which of the following is a required condition for a discrete probability function? a. ∑f(x) = 0 for all values of x b. f(x) 1 for all values of x c. f(x) < 0 for all values of x d. ∑f(x) = 1 for all values of x

d. ∑f(x) = 1 for all values of x

23. The Poisson probability distribution is used with a. a continuous random variable. b. a discrete random variable. c. either a continuous or discrete random variable. d. any random variable.

23. The Poisson probability distribution is used with a. a continuous random variable. b. a discrete random variable. c. either a continuous or discrete random variable. d. any random variable.

11. The number of customers that enter a store during one day is an example of a. a continuous random variable. b. a discrete random variable. c. either a continuous or a discrete random variable, depending on whether odd or even number of the customers enter. d. either a continuous or a discrete random variable, depending on the gender of the customers.

b. a discrete random variable.

17. The binomial probability distribution is used with a. a continuous random variable. b. a discrete random variable. c. a uniform random variable. d. an intermittent random variable.

b. a discrete random variable.

3. A probability distribution showing the probability of x successes in n trials, where the probability of success does not change from trial to trial, is termed a a. uniform probability distribution. b. binomial probability distribution. c. hypergeometric probability distribution. d. normal probability distribution.

b. binomial probability distribution.

10. An experiment consists of determining the speed of automobiles on a highway by the use of radar equipment. The random variable in this experiment is a a. discrete random variable. b. continuous random variable. c. mixed type random variable. d. multivariate random variable.

b. continuous random variable.

16. The Poisson probability distribution is a a. continuous probability distribution. b. discrete probability distribution. c. uniform probability distribution. d. normal probability distribution.

b. discrete probability distribution.

8. Which of the following is a required condition for a discrete probability function? a. f(x) 0 for all values of x b. ∑f(x) = 1 for all values of x c. ∑f(x) = 0 for all values of x d. ∑f(x) 1 for all values of x

b. ∑f(x) = 1 for all values of x